Mitogenesis Networks

有丝分裂网络

• 批准号: 8181030
• 负责人: Forest M White
• 金额: $ 105.26万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-30 至 2015-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8181030
• 关键词: Brain; Brain Neoplasms; Cancer Model; Cell Culture System; Cell model; Chemical Models; DNA Damage; Development; Epidermal Growth Factor Receptor; Family; Family member; Funding; Goals; Human; In Vitro; Kinetics; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Modeling; Mus; Mutation; Oncogenic; Patients; Phase; Pilot Projects; Protein Isoforms; Radiation; Resistance; Respiratory System; Signal Transduction; Stimulation of Cell Proliferation; Survival Rate; Testing; Therapeutic; Xenograft procedure; cell growth regulation; cell type; chemotherapeutic agent; mutant; neoplastic cell; network models; new therapeutic target; outcome forecast; receptor; response; success; therapeutic target; tumor

The overall goal of the Mitogenic Signaling Networks project is the development of high level statistical and specific physico-chemical models that describe key features of mitogenic signaling networks activated by ErbB receptors and by oncogenic K-ras. Over the past 4 years we have made significant progress in developing models of ErbB family mitogenic signaling networks in a variety of cell types, including statistical and kinetic models describing the effects of increased expression of various ErbB family members. Over the next five years we will extend these models to include mitogenic signaling networks resulting from mutant isoforms of EGFR and K-Ras that are directly associated with poor prognosis in human cancers of the central nervous and respiratory systems. Models will be developed and tested at a variety of scales, including in vitro cell culture systems, murine xenografts, and mouse cancer models. In addition, due to the success of a pilot project funded from our current ICBP, we will extend these models to integrate transcriptional regulatory networks, providing a more global, quantitative model of cellular regulation in response to oncogenic mutation. Since therapeutic resistance is one of the hallmarks of lung and brain tumors driven by mutant EGFR and mutant Ras, in the next phase of this project we will quantify and model signaling and transcriptional network alterations resulting from treatment with a variety of therapeutics, including classical chemotherapeutics, targeted therapeutics, and radiation. The goal of this project is to understand adaptation mechanisms used by tumor cells in developing therapeutic resistance in order to target these adaptive mechanisms to revert resistance. Quantitative models of mitogenic signaling network responses to therapeutics will be applied to human tumors to test their ability to predict responsiveness of human tumors to selected chemotherapeutic agents. This project will facilitate the integration of mitogenic signaling network models with DNA damage response models developed in Project 2, leading to more integrated models of cellular regulatory networks.

有丝分裂信号网络项目的总体目标是开发高水平的和特定的物理化学模型，这些模型描述了ERBB受体激活的有丝分裂信号网络和致癌K-RAS的关键特征。在过去的四年中，我们在开发各种细胞类型的ERBB家族有丝分裂信号网络的模型方面取得了重大进展，包括统计和动力学模型，描述了各种ERBB家族成员表达增加的影响。在接下来的五年中，我们将扩展这些模型，包括由EGFR和K-RAS突变同工型引起的有丝分裂信号网络，这些网络与中枢神经和呼吸系统的人类癌症的预后不良直接相关。模型将在各种尺度上开发和测试，包括体外细胞培养系统，鼠异种移植物和小鼠癌模型。此外，由于我们当前ICBP资助的试验项目的成功，我们将扩展这些模型以整合转录调节网络，从而为响应致癌突变提供了更全球的细胞调节定量模型。 由于治疗性耐药性是由突变EGFR和突变体RAS驱动的肺和脑肿瘤的标志之一，因此在该项目的下一阶段，我们将量化和模型信号传导和转录网络改变，包括多种疗法，包括经典化学治疗，靶向治疗疗法和辐射。该项目的目的是了解肿瘤细胞在发展治疗性抗性中使用的适应机制，以靶向这些适应性 恢复电阻的机制。有丝分裂信号网络对治疗剂的反应的定量模型将应用于人类肿瘤，以测试其预测人类肿瘤对选定化学治疗剂的反应能力的能力。该项目将促进将有丝分裂信号网络模型与项目2中开发的DNA损伤响应模型的整合，从而导致细胞调节网络的更集成模型。